Adding High Temporal Resolution to the Global Long-Term Aerosol Data Record: A Synergy of Low-Earth Orbit and Geostationary-Earth Orbit

The launch of Terra heralded a revolution in Earth observations. Using the 15+ years of the Earth Observing System (EOS) era, our understanding of Earth’s systems has taken a giant leap forward. For many of our EOS data records, the Visible-Infrared Observing Suite (VIIRS) and other sensors on the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite, and Joint Polar Satellite System (JPSS) will provide long-term continuity.

While the EOS and follow-on missions will continue to contribute scientifically, the only “once-or-twice-a-day” snapshots limits our understanding of these systems. In particular, our atmosphere is driven by the daily solar cycle. How do we observe diurnal information, while also keeping the global perspective provided by our EOS legacy? This need runs across many EOS-era data products, but is especially pertinent for aerosols.

The international Global Climate Observing System (GCOS) has defined six requirements as necessary for developing a Climate Data Record (CDR). A dataset that joins EOS and JPSS may be able to meet the requirements of record length, spatial resolution, accuracy, and precision, but would still be insufficient. There is an additional requirement of frequent temporal observation that cannot be met by EOS-legacy polar orbiters alone. Even if we can extend the current data set indefinitely, without increasing the frequency of observation, we can never produce an aerosol CDR.

With the advent of the third generation of geostationary satellites (GEO), e.g. Advanced Himawari Imagers (AHI) on Himawari-8 (H-8 in 2015) and H-9 (2017), and the Advanced Baseline Imager (ABI) on GOES-R/16 (2016), we are poised to bring diurnal perspective to understanding of the global aerosol system. However, GEO alone, by definition, can only produce a regional data set. Therefore, our goal is to produce a global, diurnal data set from fusion of GEO and polar-orbiting observations.

To maintain consistency across the several GEO and polar-orbiting sensors, we will apply a single aerosol-retrieving algorithm. This is the Dark Target (DT) algorithm, MODIS’ benchmark aerosol product that has been proven on VIIRS and already shows promise on AHI. We propose 3 tiers of products: a Level 2 (L2) of DT applied to GEO full disk imagery at sensor native resolution, a L2G of fused GEO and polar orbiting products on a global grid every 30 minutes, and a Level 3 that will resolve monthly mean diurnal statistics across the globe. The data sets will be archived and publicly available in netCDF format, but they will also be ingested and available through the Giovanni visualization and analysis web site, and enhance the air quality forecasting enhanced Infusing satellite Data into Environmental Applications (eIDEA) tool.

This project brings together a team of aerosol product developers, data experts, air quality scientists, and collaborators from the modeling/assimilation and aerosol transport communities, with the purpose of extending the DT aerosol record, not in terms of time series length, but in terms of temporal frequency in order to construct a true aerosol CDR. At the same time, we will produce a new product from a well-validated mature product that will give researchers and applied scientists across many sub-disciplines the next giant leap forward in understanding the global aerosol system.